Datasets:
Create README.md
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README.md
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---
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dataset_info:
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features:
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- name: image
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dtype: image
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- name: question_id
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dtype: int64
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- name: question
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dtype: string
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- name: answers
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sequence: string
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- name: data_split
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dtype: string
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- name: ocr_results
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struct:
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- name: page
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dtype: int64
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- name: clockwise_orientation
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dtype: float64
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- name: width
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dtype: int64
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- name: height
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dtype: int64
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- name: unit
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dtype: string
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- name: lines
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list:
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- name: bounding_box
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sequence: int64
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- name: text
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dtype: string
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- name: words
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list:
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- name: bounding_box
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sequence: int64
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- name: text
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dtype: string
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- name: confidence
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dtype: string
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- name: other_metadata
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struct:
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- name: ucsf_document_id
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dtype: string
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- name: ucsf_document_page_no
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dtype: string
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- name: doc_id
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dtype: int64
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- name: image
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dtype: string
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splits:
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- name: train
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num_examples: 39463
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- name: validation
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num_examples: 5349
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- name: test
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num_examples: 5188
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: validation
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path: data/validation-*
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- split: test
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path: data/test-*
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license: mit
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task_categories:
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- question-answering
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language:
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- en
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pretty_name: d
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size_categories:
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- 10K<n<100K
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---
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# Dataset Card for DocVQA Dataset
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## Dataset Description
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- **Point of Contact from curators:** [Minesh Mathew](mailto:minesh.mathew@gmail.com), [Dimosthenis Karatzas](dimos@cvc.uab.es), [C. V. Jawahar](jawahar@iiit.ac.in)
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- **Point of Contact Hugging Face:** [Pablo Montalvo](mailto:pablo@huggingface.co)
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### Dataset Summary
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DocVQA dataset is a document dataset introduced in Mathew et al. (2021) consisting of 50,000 questions defined on 12,000+ document images.
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### Usage
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This dataset can be used with current releases of Hugging Face `datasets` library.
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Here is an example using a custom collator to bundle batches in a trainable way on the `train` split
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```python
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from datasets import load_dataset
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docvqa_dataset = load_dataset("pixparse/docvqa-single-page", split="train"
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)
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collator_class = Collator()
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loader = DataLoader(docvqa_dataset, batch_size=8, collate_fn=collator_class.collate_fn)
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```
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The loader can then be iterated on normally and yields image + question and answer samples.
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### Data Splits
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#### Train
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* 10194 images, 39463 questions and answers.
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### Validation
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* 1286 images, 5349 questions and answers.
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### Test
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* 1,287 images, 5,188 questions.
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## Additional Information
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### Dataset Curators
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Pablo Montalvo, Ross Wightman
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### Licensing Information
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MIT
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### Citation Information
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Mathew, Minesh, Dimosthenis Karatzas, and C. V. Jawahar. "Docvqa: A dataset for vqa on document images." Proceedings of the IEEE/CVF winter conference on applications of computer vision. 20
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